What do you do if your AI solutions aren't effectively communicating their impact on business outcomes?

Any communication includes two elements - The content and delivery. Typically technologists are not great communicators because of the way in which they deliver the message. They leave a lot for the receiver to decipher. However in the case of the impact of AI, the business is typically eager to listen. So the real question is about is there content that grabs the attention of the business. Are people doing AI projects for the sake of proving the concept or are they creating a business impact leveraging the technology. Any thoughts ?

Here is a very simple exercise -- for both life and AI solution. What will the tombstone say? Before you start building the project, write a news story covering the success of your project [after it is built]. What will be the headline of that story? Once you understand what that headline should be and get an acceptance from everyone in the team that is the right way to look at the project it is easy to build the project.

1. Identify key performance indicators (KPIs) that align with business goals and track the AI solution's impact on those metrics. 2. Use data visualization tools to present the AI's performance in a clear and compelling way, highlighting improvements in areas like efficiency, cost savings, revenue growth, etc. 3. Conduct regular reviews with stakeholders, sharing success stories and concrete examples of how the AI has driven positive outcomes. 4. Gather feedback from end-users to understand pain points and areas where the AI's value proposition may not be clearly understood. 5. Develop a comprehensive communication strategy that articulates the AI's benefits in language that resonates with different audiences across the organization.

If my solution is not as per the required business need then to address limitations in AI solutions, it's essential to combine human intellect with AI capabilities. This involves understanding the scope of the project, conducting market research, and considering factors beyond the AI model's current understanding. Relying solely on system-generated solutions may limit the effectiveness of AI in meeting business needs. By combining human creativity and problem-solving skills with AI capabilities, organizations can develop innovative solutions that better align with business objectives.

To ensure your AI solutions effectively communicate their impact on business outcomes, start by defining clear and measurable KPIs aligned with business objectives. Implement robust tracking mechanisms and utilize data visualization techniques to present impact clearly. Provide context around metrics and solicit feedback from stakeholders to tailor communication. This transparency enhances effectiveness and drives adoption within the organization.

To enhance understanding, refine the metrics for measuring AI success to align with business goals. Rather than technical metrics, focus on those directly reflecting business objectives. For instance, if an AI system aims to streamline inventory management, measure success through reduced inventory costs or improved stock turnover rates. These metrics better communicate the AI's impact on the business.

Refining the metrics used to measure AI success is a critical step in bridging the gap between the technical capabilities of AI systems and the business outcomes they are meant to enhance. To make AI metrics more relevant and understandable to business stakeholders, it is important to focus on indicators that directly tie into business goals. Further, by aligning AI metrics with business objectives, stakeholders can more easily see the value of AI investments and make informed decisions about where to allocate resources.

Refine AI success metrics to align with business objectives: Focus on Business Metrics: Transition from technical metrics like precision to those reflecting business goals. Measure Relevant Outcomes: For AI in inventory management, track metrics such as reduction in inventory costs and improvement in stock turnover rates. Communicate AI Impact: Use business-centric metrics to clearly demonstrate AI's value to stakeholders, bridging the gap between technical performance and business benefits. This approach ensures AI contributions are evaluated in a context that resonates with business stakeholders, enhancing understanding and appreciation of its benefits.

Engage teams and identify champions in your organization who will support AI implementations. Also, determine who is resistant to the technology and devise strategies to address this resistance (i.e., are there skills gaps that need to be addressed?). Lastly, ensure continuous communication among stakeholders to maintain clarity on challenges and successes.

This mutual understanding is crucial for aligning AI developments with business needs and for maximizing the technology's impact. Collaboration between these teams facilitates the creation of tailored tools such as custom reports and dashboards that are designed to make sense of AI data in the context of business goals. Moreover, involving diverse teams from different functions such as finance, marketing, operations, and customer service ensures that the AI's benefits are evaluated from various perspectives. This diversity enriches the narrative around the AI's business impact, highlighting different benefits such as cost savings, improved customer engagement, or enhanced decision-making speed and accuracy.

Engaging cross-functional teams is crucial for improving communication. Encourage ongoing dialogue between AI developers and business units to ensure mutual understanding of goals and capabilities. This collaboration can lead to the development of custom reports or dashboards that translate AI activities into business insights. Involving diverse teams enriches the narrative around the AI's business impact.

Engaging cross-functional teams is key to maximizing AI’s business impact: Encourage Dialogue: Promote ongoing conversations between AI developers and business units to align goals and share insights. Create Collaborative Tools: Develop custom reports or dashboards that translate AI’s technical activities into business-relevant insights. Include Diverse Perspectives: Ensure involvement from various departments to broaden the understanding of AI’s impact. Enhance Narrative: This approach deepens the narrative around AI’s benefits, showing its value through different business lenses. This strategy helps bridge communication gaps and ensures that AI’s contributions are fully understood and appreciated across the organization.

??Considere sua IA como um guia turístico em uma cidade estrangeira. Os líderes de negócios s?o os turistas, e a cidade é o mundo complexo e muitas vezes confuso da IA. Como guia turístico, o trabalho da sua IA n?o é apenas mostrar os pontos turísticos (ou seja, os resultados), mas também traduzir a cultura local (ou seja, os jarg?es e conceitos de IA) de uma forma que os turistas possam entender e apreciar. ??Como um bom guia turístico, a sua IA também deve ser capaz de “ouvir” os turistas. Isso significa entender as suas necessidades, preocupa??es e interesses, e ajustar a “visita guiada” de acordo. ? A comunica??o sob medida na IA n?o é apenas sobre falar, mas sobre 'traduzir e ouvir'. #ai #ia

When Communication among teams or with others, we need to keep in mind following points: 1) Avoid Technical Jargon 2) Utilize Visual Aids 3) Tell Compelling Stories 4) Highlight Case Studies/Succinct Examples 5) Focus on End Results 6) Engage Through Regular Updates 7) Solicit Feedback for Improvement

A brilliant tool that can help communicate with leadership is the machine learning model canvas (by Goku Mohandas). The similarity with the Business Model canvas makes it easier for them to understand and relate to how their business problem was framed into an ML problem

Tailoring your communication to make AI outcomes accessible to business leaders is crucial: Avoid Jargon: Simplify your language to ensure clarity and avoid alienating stakeholders who may not be familiar with AI terminology. Use Visual Aids: Employ graphs, charts, or infographics to visually demonstrate how AI contributes to business improvements. Tell Stories: Craft narratives that show how AI solves specific business problems or captures new opportunities, making its benefits tangible and relatable. Make It Relevant: Present AI data and results in a context that resonates with business leaders’ priorities and concerns. By adapting your communication approach, you enhance stakeholders' understanding and engagement.

Para comunicar efectivamente el impacto de tus soluciones de IA, adopta una estrategia de comunicación a medida. Identifica a tus distintas audiencias clave, como ejecutivos, equipos técnicos y clientes, y adapta tus mensajes para abordar sus necesidades e intereses específicos. Utiliza un lenguaje claro y conciso, respaldado por datos y métricas relevantes, al comunicarte con líderes empresariales. Para audiencias técnicas, profundiza en los detalles técnicos y los desafíos superados. Con los clientes, enfatiza los beneficios tangibles y la mejora en la experiencia del usuario.

≒?Muitas vezes, a falta de impacto percebido n?o está na eficácia da IA, mas sim na *falta de conex?o humana* com essa tecnologia. Sugest?o: ? Dê um nome e uma personalidade à IA. Isso a torna mais acessível e menos abstrata para as pessoas. ? Crie um blog ou vlog em nome da IA, onde ela "conversa" sobre seu trabalho, desafios e sucessos. Use um tom informal e humorístico para quebrar barreiras. ? Promova intera??es entre a "IA personagem" e os funcionários. Sess?es de perguntas e respostas, enquetes e até mesmo jogos podem fortalecer a conex?o e a compreens?o da IA. #ai #ia

This approach involves regularly collecting and incorporating feedback from various business stakeholders to refine both the AI models themselves and the methods used to report and communicate their outcomes. By integrating this feedback, organizations can adapt and evolve their AI systems to better serve current business needs and anticipate future requirements. This continuous loop of feedback and improvement is crucial for leveraging AI as a dynamic tool for business innovation and efficiency.

If AI solutions aren't effectively communicating their impact, consider fostering a more transparent and collaborative environment. Openly discuss challenges with implementation and actively solicit feedback from stakeholders. This two-way dialogue can help identify areas for improvement and refine the AI's capabilities to better align with real-world business needs. Additionally, involving stakeholders in the solution's development fosters a sense of ownership and increases their investment in its success.

AI solutions aren't effectively communicating their impact on business outcomes, nothing to worry. The following steps can be taken like: ??Review data inputs and outputs for discrepancies ?? Fine-tune algorithms for better accuracy and relevance ?? Use dashboards and visualizations to make insights clearer ?? Translate technical jargon into understandable language for stakeholders ?? Continuously update and improve the AI system based on feedback and performance metrics

AI Solutions are new and it a unchartered domain for all of us. Any AI project needs commitment from the senior leadership. Expectations including ROI and project outcomes must be written down. Don't aim for the sky. Like any technology implementation (especially when implementing a brand new technology), conduct a PoC and systematically set the realistic expectations with the mangement. Have a mechanism to measure your success. Or Run your AI in parallel to the legacy process. Then it is easy to compare apples to apples. For example: "Mia successfully flagged all cases with symptoms of breast cancer, including an additional 11 cases that were not identified by doctors."

AI's impact on business outcomes can be sometimes unclear. The key to solve this is through clear communication and value proposition. Focus on translating AI into actionable steps. Explain how these insights improve processes and ultimately the bottom line. This allows AI's power to be understood by customers, and therefore unlock its true business potential.

Show Don’t Tell: Use clear, concise data and visual aids to demonstrate the AI's impact. Align AI Metrics with Business Goals: Ensure the AI’s objectives are directly tied to key business outcomes. Communicate Regularly: Keep stakeholders informed through regular updates and open channels of communication. Educate Your Audience: Help stakeholders understand how the AI works and how it makes decisions. Be Responsive: Adjust AI strategies based on stakeholder feedback to better meet business needs.